In this paper, a numerical approximation for a time fractional one-dimensional bioheat equation (transfer paradigm) of temperature distribution in tissues is introduced. It deals with the Caputo fractional derivative with order for time fractional derivative and new mixed nonpolynomial spline for second order of space derivative. We also analyzed the convergence and stability by employing Von Neumann method for the present scheme.

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     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

Most dental supplies don't seem to be much of a barrier against germ infiltration. Therefore, the filling must be done with perfect caution and high antimicrobial effectiveness. When dental erosion occurs due to germs that lead to caries, a dental filling is used, creating a small microscopic space between the dental filling and the root end infiltration. This allowed the tooth to be penetrated for the second time, which was the research problem. Adding two compounds to antibacterial fillers (zinc polycarboxylate cement) made them work better: Firstly, was zinc oxide  (ZnO) that was made chemically, and secondly, was green ZnO nanoparticles that were made from orange peels and mixed with ZPCC in different amounts. The study was conducte

     The proton, neutron and matter density distributions, the corresponding size radii and elastic electron scattering form factors of one-proton⁸B and two-proton ¹⁷Ne halo nuclei are calculated. The theoretical technique used to fulfill calculations is by assuming that both nuclei under study are composed of two main parts; the first is the compact core and the second is the unstable halo part. The single-particle radial wavefunctions of harmonic-oscillator (HO) and Woods-Saxon (WS) potentials are used to study core and halo parts, respectively. And other approach is studied by using HO potential for both core and halo parts, but using two HO size parameters for both supposed parts. The long ta

The thin films of cadmium oxide (CdO) were deposited using the SILAR (Successive ionic layer absorption and reaction) method at various deposition cycles. CdO thin films were made on glass substrates at a temperature of  95°C, using a cadmium acetate source material and an ammonium hydroxide solution. One of the main criteria that impact the quality of thin films is the number of deposition cycles. The size of the crystals decreases with the increase in the number of cycles from 33.7 nm at the immersion cycle 10 to 22.7 nm at the immersion cycle 20, as shown by the X-ray diffraction results. The optical band gap energy of the films reduces as the number of deposition cycles increases, while the transmittance of the Cadmium oxide film i

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r